{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scores for Weyn et al 2020\n",
    "\n",
    "WeatherBench scores for https://www.essoar.org/doi/10.1002/essoar.10502543.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "from src.regrid import *\n",
    "from src.score import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATADIR = '/data/stephan/WeatherBench/5.625deg/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "z500_valid = load_test_data(f'{DATADIR}geopotential_500', 'z')\n",
    "t850_valid = load_test_data(f'{DATADIR}temperature_850', 't')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1st file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_raw = xr.open_dataset('/data/stephan/Weyn/forecast_dlwp-cs_WeatherBench.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.Dataset&gt;\n",
       "Dimensions:     (f_hour: 56, lat: 91, lon: 180, time: 418)\n",
       "Coordinates:\n",
       "  * lon         (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0\n",
       "  * lat         (lat) float64 89.01 87.03 85.05 83.08 ... -85.05 -87.03 -89.01\n",
       "  * f_hour      (f_hour) float64 6.0 12.0 18.0 24.0 ... 318.0 324.0 330.0 336.0\n",
       "  * time        (time) datetime64[ns] 2017-01-01 ... 2018-12-30T12:00:00\n",
       "Data variables:\n",
       "    z500        (f_hour, time, lat, lon) float32 ...\n",
       "    tau300-700  (f_hour, time, lat, lon) float32 ...\n",
       "    z1000       (f_hour, time, lat, lon) float32 ...\n",
       "    t2m         (f_hour, time, lat, lon) float32 ...</pre>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:     (f_hour: 56, lat: 91, lon: 180, time: 418)\n",
       "Coordinates:\n",
       "  * lon         (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0\n",
       "  * lat         (lat) float64 89.01 87.03 85.05 83.08 ... -85.05 -87.03 -89.01\n",
       "  * f_hour      (f_hour) float64 6.0 12.0 18.0 24.0 ... 318.0 324.0 330.0 336.0\n",
       "  * time        (time) datetime64[ns] 2017-01-01 ... 2018-12-30T12:00:00\n",
       "Data variables:\n",
       "    z500        (f_hour, time, lat, lon) float32 ...\n",
       "    tau300-700  (f_hour, time, lat, lon) float32 ...\n",
       "    z1000       (f_hour, time, lat, lon) float32 ...\n",
       "    t2m         (f_hour, time, lat, lon) float32 ..."
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Create weight file: bilinear_91x180_32x64_peri.nc\n",
      "using dimensions ('lat', 'lon') from data variable z500 as the horizontal dimensions for this dataset.\n",
      "using dimensions ('lat', 'lon') from data variable z500 as the horizontal dimensions for this dataset.\n"
     ]
    }
   ],
   "source": [
    "ds = regrid(ds_raw, ddeg_out=5.625)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fd0e1964950>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.z500.isel(f_hour=-1, time=-1).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = ds.rename({'f_hour': 'lead_time'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "rmses = evaluate_iterative_forecast(ds.z500, z500_valid).compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.DataArray &#x27;rmse&#x27; (lead_time: 2)&gt;\n",
       "array([388.05496707, 623.93437454])\n",
       "Coordinates:\n",
       "    level      int32 500\n",
       "  * lead_time  (lead_time) float64 72.0 120.0</pre>"
      ],
      "text/plain": [
       "<xarray.DataArray 'rmse' (lead_time: 2)>\n",
       "array([388.05496707, 623.93437454])\n",
       "Coordinates:\n",
       "    level      int32 500\n",
       "  * lead_time  (lead_time) float64 72.0 120.0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmses.sel(lead_time=[72, 120])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fd0b22ffb50>]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rmses.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2nd File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_raw = xr.open_dataset('/data/stephan/Weyn/forecast_dlwp-cs-s2s_4var-t850_UNET2.1_WeatherBench.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<defs>\n",
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       "<title>Show/Hide data repr</title>\n",
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       "<title>Show/Hide attributes</title>\n",
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       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
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       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
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       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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       "\n",
       ".xr-wrap {\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
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       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
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       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
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       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
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       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-cdc6213f-0b7a-4fa3-b1c2-e6acc507897d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cdc6213f-0b7a-4fa3-b1c2-e6acc507897d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>f_hour</span>: 56</li><li><span class='xr-has-index'>lat</span>: 91</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>time</span>: 418</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-823a9bee-dd75-4b02-932a-b4e2111c66fa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-823a9bee-dd75-4b02-932a-b4e2111c66fa' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-6bb1591d-af82-4655-90a2-92d3b41117f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6bb1591d-af82-4655-90a2-92d3b41117f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b270aa5-b04e-4d40-ad89-46452f547c00' class='xr-var-data-in' type='checkbox'><label for='data-4b270aa5-b04e-4d40-ad89-46452f547c00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>89.01 87.03 85.05 ... -87.03 -89.01</div><input id='attrs-3c576c1d-74d1-4f34-8ca4-3c41dc4af97c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c576c1d-74d1-4f34-8ca4-3c41dc4af97c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-543754bb-8449-4089-8034-20d677a61968' class='xr-var-data-in' type='checkbox'><label for='data-543754bb-8449-4089-8034-20d677a61968' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><pre class='xr-var-data'>array([ 89.010989,  87.032967,  85.054945,  83.076923,  81.098901,  79.120879,\n",
       "        77.142857,  75.164835,  73.186813,  71.208791,  69.230769,  67.252747,\n",
       "        65.274725,  63.296703,  61.318681,  59.340659,  57.362637,  55.384615,\n",
       "        53.406593,  51.428571,  49.450549,  47.472527,  45.494505,  43.516484,\n",
       "        41.538462,  39.56044 ,  37.582418,  35.604396,  33.626374,  31.648352,\n",
       "        29.67033 ,  27.692308,  25.714286,  23.736264,  21.758242,  19.78022 ,\n",
       "        17.802198,  15.824176,  13.846154,  11.868132,   9.89011 ,   7.912088,\n",
       "         5.934066,   3.956044,   1.978022,   0.      ,  -1.978022,  -3.956044,\n",
       "        -5.934066,  -7.912088,  -9.89011 , -11.868132, -13.846154, -15.824176,\n",
       "       -17.802198, -19.78022 , -21.758242, -23.736264, -25.714286, -27.692308,\n",
       "       -29.67033 , -31.648352, -33.626374, -35.604396, -37.582418, -39.56044 ,\n",
       "       -41.538462, -43.516484, -45.494505, -47.472527, -49.450549, -51.428571,\n",
       "       -53.406593, -55.384615, -57.362637, -59.340659, -61.318681, -63.296703,\n",
       "       -65.274725, -67.252747, -69.230769, -71.208791, -73.186813, -75.164835,\n",
       "       -77.142857, -79.120879, -81.098901, -83.076923, -85.054945, -87.032967,\n",
       "       -89.010989])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>f_hour</span></div><div class='xr-var-dims'>(f_hour)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.0 12.0 18.0 ... 324.0 330.0 336.0</div><input id='attrs-1a7d412a-a1fb-42dc-84f1-eb2aca2cf70f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a7d412a-a1fb-42dc-84f1-eb2aca2cf70f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c9c2e90-d183-401f-8f0d-1ad3cb257e1b' class='xr-var-data-in' type='checkbox'><label for='data-0c9c2e90-d183-401f-8f0d-1ad3cb257e1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([  6.,  12.,  18.,  24.,  30.,  36.,  42.,  48.,  54.,  60.,  66.,  72.,\n",
       "        78.,  84.,  90.,  96., 102., 108., 114., 120., 126., 132., 138., 144.,\n",
       "       150., 156., 162., 168., 174., 180., 186., 192., 198., 204., 210., 216.,\n",
       "       222., 228., 234., 240., 246., 252., 258., 264., 270., 276., 282., 288.,\n",
       "       294., 300., 306., 312., 318., 324., 330., 336.])</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2017-01-01 ... 2018-12-30T12:00:00</div><input id='attrs-c8dc00ad-53ba-491f-a95f-2566164d27ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c8dc00ad-53ba-491f-a95f-2566164d27ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52d5b227-dfc8-4c15-980b-de4d7c96e764' class='xr-var-data-in' type='checkbox'><label for='data-52d5b227-dfc8-4c15-980b-de4d7c96e764' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sample start time</dd></dl></div><pre class='xr-var-data'>array([&#x27;2017-01-01T00:00:00.000000000&#x27;, &#x27;2017-01-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;2017-01-04T00:00:00.000000000&#x27;, ..., &#x27;2018-12-26T12:00:00.000000000&#x27;,\n",
       "       &#x27;2018-12-30T00:00:00.000000000&#x27;, &#x27;2018-12-30T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></li></ul></div></li><li class='xr-section-item'><input id='section-4e209689-963b-4955-8842-a2ca77d45a24' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4e209689-963b-4955-8842-a2ca77d45a24' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>z500</span></div><div class='xr-var-dims'>(f_hour, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-50153010-c1cb-412c-8e26-28dafccd5a8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50153010-c1cb-412c-8e26-28dafccd5a8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d87f95a-726f-4aaf-a3ba-a3c5764f5e67' class='xr-var-data-in' type='checkbox'><label for='data-7d87f95a-726f-4aaf-a3ba-a3c5764f5e67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinates :</span></dt><dd>height width face</dd></dl></div><pre class='xr-var-data'>[383423040 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>tau300-700</span></div><div class='xr-var-dims'>(f_hour, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ac025a1a-7cc5-4eab-8d53-2cdb88a00a01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac025a1a-7cc5-4eab-8d53-2cdb88a00a01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d98c121d-5a8f-44c3-a2df-1b24b56cbb56' class='xr-var-data-in' type='checkbox'><label for='data-d98c121d-5a8f-44c3-a2df-1b24b56cbb56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinates :</span></dt><dd>height width face</dd></dl></div><pre class='xr-var-data'>[383423040 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>z1000</span></div><div class='xr-var-dims'>(f_hour, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9d6908b6-7250-4866-a7d5-78225ce7d79b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d6908b6-7250-4866-a7d5-78225ce7d79b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-652df970-c806-49a1-87fe-9b5887a9a004' class='xr-var-data-in' type='checkbox'><label for='data-652df970-c806-49a1-87fe-9b5887a9a004' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinates :</span></dt><dd>height width face</dd></dl></div><pre class='xr-var-data'>[383423040 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>t2m0</span></div><div class='xr-var-dims'>(f_hour, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ba825b3c-8fbf-4fa7-abf7-cabd133f178c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba825b3c-8fbf-4fa7-abf7-cabd133f178c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1f37f35-a1cf-4291-a08c-0657487573a7' class='xr-var-data-in' type='checkbox'><label for='data-d1f37f35-a1cf-4291-a08c-0657487573a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinates :</span></dt><dd>height width face</dd></dl></div><pre class='xr-var-data'>[383423040 values with dtype=float32]</pre></li><li class='xr-var-item'><div class='xr-var-name'><span>t850</span></div><div class='xr-var-dims'>(f_hour, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1284d3dc-4f81-4c1e-b465-eaf0e5c57678' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1284d3dc-4f81-4c1e-b465-eaf0e5c57678' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-023a770f-5fa9-43a8-bfd2-3c72bf7ff37b' class='xr-var-data-in' type='checkbox'><label for='data-023a770f-5fa9-43a8-bfd2-3c72bf7ff37b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinates :</span></dt><dd>height width face</dd></dl></div><pre class='xr-var-data'>[383423040 values with dtype=float32]</pre></li></ul></div></li><li class='xr-section-item'><input id='section-de62ee6f-1f66-40d3-8fd9-59fffe67dd66' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-de62ee6f-1f66-40d3-8fd9-59fffe67dd66' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:     (f_hour: 56, lat: 91, lon: 180, time: 418)\n",
       "Coordinates:\n",
       "  * lon         (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0\n",
       "  * lat         (lat) float64 89.01 87.03 85.05 83.08 ... -85.05 -87.03 -89.01\n",
       "  * f_hour      (f_hour) float64 6.0 12.0 18.0 24.0 ... 318.0 324.0 330.0 336.0\n",
       "  * time        (time) datetime64[ns] 2017-01-01 ... 2018-12-30T12:00:00\n",
       "Data variables:\n",
       "    z500        (f_hour, time, lat, lon) float32 ...\n",
       "    tau300-700  (f_hour, time, lat, lon) float32 ...\n",
       "    z1000       (f_hour, time, lat, lon) float32 ...\n",
       "    t2m0        (f_hour, time, lat, lon) float32 ...\n",
       "    t850        (f_hour, time, lat, lon) float32 ..."
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reuse existing file: bilinear_91x180_32x64_peri.nc\n",
      "using dimensions ('lat', 'lon') from data variable z500 as the horizontal dimensions for this dataset.\n",
      "using dimensions ('lat', 'lon') from data variable z500 as the horizontal dimensions for this dataset.\n"
     ]
    }
   ],
   "source": [
    "ds = regrid(ds_raw, ddeg_out=5.625)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fd0264a9310>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.t850.isel(f_hour=-1, time=-1).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = ds.rename({'f_hour': 'lead_time'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "rmses = evaluate_iterative_forecast(ds.z500, z500_valid).compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  6.,  12.,  18.,  24.,  30.,  36.,  42.,  48.,  54.,  60.,  66.,\n",
       "        72.,  78.,  84.,  90.,  96., 102., 108., 114., 120., 126., 132.,\n",
       "       138., 144., 150., 156., 162., 168., 174., 180., 186., 192., 198.,\n",
       "       204., 210., 216., 222., 228., 234., 240., 246., 252., 258., 264.,\n",
       "       270., 276., 282., 288., 294., 300., 306., 312., 318., 324., 330.,\n",
       "       336.])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmses.lead_time.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 103.17063188,  122.10630367,  136.10243211,  159.60371898,\n",
       "        178.83708591,  206.70160156,  229.36348603,  258.81130062,\n",
       "        283.71891857,  314.78230398,  341.39132258,  373.37219594,\n",
       "        401.58606025,  434.29952685,  463.15802549,  495.80006639,\n",
       "        524.31388468,  555.66859751,  582.47058652,  611.33059846,\n",
       "        635.65855631,  661.66887225,  683.22820212,  707.28077907,\n",
       "        726.94251408,  748.87247504,  766.51542843,  786.40857263,\n",
       "        802.06248032,  820.28514369,  834.91832605,  852.20249022,\n",
       "        865.43747786,  881.59577428,  893.30422587,  907.57530058,\n",
       "        917.48300651,  929.24543796,  937.19334574,  947.70628695,\n",
       "        954.58220955,  964.02763426,  970.54550441,  980.02610941,\n",
       "        986.14846482,  995.15838525, 1000.47042489, 1008.57077913,\n",
       "       1013.20967844, 1020.09060853, 1023.76321382, 1030.14072867,\n",
       "       1032.59675919, 1037.47101357, 1039.05914728, 1043.93011695])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmses.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'rmse'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lead_time</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d797f2f7-3f4d-4f22-9a0c-0010e37005dc' class='xr-array-in' type='checkbox' ><label for='section-d797f2f7-3f4d-4f22-9a0c-0010e37005dc' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>373.4 611.3</span></div><pre class='xr-array-data'>array([373.37219594, 611.33059846])</pre></div></li><li class='xr-section-item'><input id='section-bd6e7965-41b2-4690-b1a3-9ae98bc8fb31' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bd6e7965-41b2-4690-b1a3-9ae98bc8fb31' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>500</div><input id='attrs-ac84a2ad-5589-4823-afda-075a13d2f9d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac84a2ad-5589-4823-afda-075a13d2f9d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f66d76d-81ff-4efe-86a0-0d2948774ad0' class='xr-var-data-in' type='checkbox'><label for='data-5f66d76d-81ff-4efe-86a0-0d2948774ad0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><pre class='xr-var-data'>array(500, dtype=int32)</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lead_time</span></div><div class='xr-var-dims'>(lead_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>72.0 120.0</div><input id='attrs-d5bb42d2-3562-4b4a-9a49-ae7fbb4bdd23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5bb42d2-3562-4b4a-9a49-ae7fbb4bdd23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bca50a3-d0ec-4f01-9f22-9eccf9104fea' class='xr-var-data-in' type='checkbox'><label for='data-0bca50a3-d0ec-4f01-9f22-9eccf9104fea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([ 72., 120.])</pre></li></ul></div></li><li class='xr-section-item'><input id='section-2688e7dc-c248-4a3c-ac3c-35e35b11dcac' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2688e7dc-c248-4a3c-ac3c-35e35b11dcac' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'rmse' (lead_time: 2)>\n",
       "array([373.37219594, 611.33059846])\n",
       "Coordinates:\n",
       "    level      int32 500\n",
       "  * lead_time  (lead_time) float64 72.0 120.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmses.sel(lead_time=[72, 120])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fd0007f1450>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rmses.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "rmses = evaluate_iterative_forecast(ds.t850, t850_valid).compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.03795918, 1.15878117, 1.22158419, 1.29490652, 1.35380706,\n",
       "       1.43916452, 1.50264995, 1.59691888, 1.67583619, 1.78102905,\n",
       "       1.86647818, 1.97919404, 2.07536937, 2.1990173 , 2.30110702,\n",
       "       2.42429442, 2.52710765, 2.64945138, 2.75187673, 2.86765323,\n",
       "       2.96385755, 3.06689935, 3.15067605, 3.24370726, 3.31685812,\n",
       "       3.40008735, 3.4598297 , 3.53341098, 3.58535642, 3.65611831,\n",
       "       3.70793333, 3.77767185, 3.82740362, 3.88753727, 3.93220208,\n",
       "       3.98510661, 4.017722  , 4.05863569, 4.08302686, 4.12255695,\n",
       "       4.14510952, 4.18557443, 4.20727425, 4.2476083 , 4.2679379 ,\n",
       "       4.30476918, 4.32228166, 4.34863132, 4.36193909, 4.38523755,\n",
       "       4.39565933, 4.41983848, 4.42832529, 4.45316435, 4.45961558,\n",
       "       4.48041654])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmses.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<title>Show/Hide data repr</title>\n",
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       "\n",
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       "</style><div class='xr-wrap'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'rmse'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lead_time</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3ef1a019-f71b-4bf3-a776-e486da564fa9' class='xr-array-in' type='checkbox' ><label for='section-3ef1a019-f71b-4bf3-a776-e486da564fa9' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.979 2.868</span></div><pre class='xr-array-data'>array([1.97919404, 2.86765323])</pre></div></li><li class='xr-section-item'><input id='section-3a64f39a-c4de-4e45-ae5a-1be2027d85ce' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3a64f39a-c4de-4e45-ae5a-1be2027d85ce' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>850</div><input id='attrs-8234dc3b-faab-4e35-b8a3-b6a85aa4b51d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8234dc3b-faab-4e35-b8a3-b6a85aa4b51d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-757cd470-e84a-4b41-af76-b19de40cb7f6' class='xr-var-data-in' type='checkbox'><label for='data-757cd470-e84a-4b41-af76-b19de40cb7f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><pre class='xr-var-data'>array(850, dtype=int32)</pre></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lead_time</span></div><div class='xr-var-dims'>(lead_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>72.0 120.0</div><input id='attrs-ee100e3c-c99b-43c9-a8b3-afa6fbf63afe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee100e3c-c99b-43c9-a8b3-afa6fbf63afe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af998f30-71fe-4747-80d8-a17657d6acf8' class='xr-var-data-in' type='checkbox'><label for='data-af998f30-71fe-4747-80d8-a17657d6acf8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><pre class='xr-var-data'>array([ 72., 120.])</pre></li></ul></div></li><li class='xr-section-item'><input id='section-07e1202c-9262-4fa6-82a5-847b59e85159' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-07e1202c-9262-4fa6-82a5-847b59e85159' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'rmse' (lead_time: 2)>\n",
       "array([1.97919404, 2.86765323])\n",
       "Coordinates:\n",
       "    level      int32 850\n",
       "  * lead_time  (lead_time) float64 72.0 120.0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rmses.sel(lead_time=[72, 120])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fd0200b2210>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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0919VWudk4K/Amuiit939waAyidS0wuJSnp68mqenrKa4tJxLB3dh9Km9NIWoJI0g9ySKgVPcvdDMUoAvzewDd59Wab0p7n5OgDlEApG1NodbX5nD1vwiRhzbgbvOOEqHliTpBFYS7u5AYfRhSvTmQb2fSG1xd56ZsoaHP1xK51aNefu/vsXArq3CjiUSiEDPSZhZfWAW0BN4wt2nV7HacDObB2wG7nL3RUFmEvkm8vaW8NM35vHx4m2c2bcDj1zSn+apKWHHEglMoCXh7mXA8WbWEnjHzPq5+8IKq8wGMqKHpEYA7wK9Kn8fMxsFjALo2rVrkJFFYlq4KY//enk2m3P3cu/Zx3D9id01WqskvVqZRd3dc4HPgTMrLc9398Lo/feBFDNLr+L1Y909090z27bVJCxSu0rKyhk7eRUXPvVPSsrKee1Hw7jhpB4qCKkTgry6qS1Q4u65ZtYYOA34XaV1OgDb3N3NbAiR0toZVCaRQzV7/S7ufnsBS7cWcNox7fjdRf1pk9Yo7FgitSbIw00dgRei5yXqAa+7+0QzuwnA3ccAFwM3m1kpsBe4NHrCWyRUeXtLeOTDpbwyYz3tm6Uy5spBfK9ve+09SJ1jifY7OTMz07OyssKOIUls4vzN3P/eYnJ2FzPyhO78+PTepGnMJUlwZjbL3TMP9XX6P18kqrzceeSjZYz5YhXHdW7BuJGD6depRdixREKlkhABikrK+Mnr8/j7gi1cMbQrD5zblwb1a+W6DpG4ppKQOm9nYTE3vpjF7PW53D3iaG7UlUsi/6KSkDptVXYhI5+fybb8Ip66YiBnHdsx7EgicUUlIXXWP1fu4OaXZ9OgnvHqqGEaWkOkCioJqXPKy50nJq3kj/9YTvf0pjx/7RC6tmkSdiyRuKSSkDolZ/c+7nhtLpOXZ3PucUfw2wuP1ZSiIgegnw6pM2atiwztvbNwH785vx9XDO2qE9QiB6GSkKTn7jz75Roe/mApR7SMDO2tzz+IVI9KQpKau/PwB0v5y+TVnNGnPf97yXG0aKyhvUWqSyUhSau83Hngb4t4Yeo6rhzWlQfP7Ue9ejq8JHIoVBKSlMrKnXveWcCEmRu44cTu3HP2MTr/IHIYVBKSdErLyvnpm/N5Z84mbjulJ3ee3lsFIXKYVBKSVErKyrljwlz+vmALd53Rm1tP+dpEhyJyCFQSkjQKi0u55eXZfLE8m3vPPoYbTuoRdiSRhKeSkKSwNa+I68bNZNm2An574bFcNkRzoYvUBJWEJLwlW/K5btxM8veW8Ow1mZx8VLuwI4kkDZWEJLTJy7P5r5dn07RRfV6/aTh9j9CH5ERqkkpCEtbrMzdw9zsL6NkujeeuHcwRLRuHHUkk6agkJCG9Mn09d7+zgJN6pfPkFQNplqpPUYsEIbD5Gc0s1cxmmNk8M1tkZg9UsY6Z2WNmttLM5pvZwKDySPJ4b95m7nl3Ad89qi3PXjNYBSESoCD3JIqBU9y90MxSgC/N7AN3n1ZhnbOAXtHbUOCp6FeRKk1aup07X5vL4IzWPHnFIBo20DzUIkEK7CfMIwqjD1OiN6+02nnAi9F1pwEtzUzzR0qVpq/eyU3jZ3F0x2Y8c20mjRvWDzuSSNIL9M8wM6tvZnOB7cAn7j690iqdgA0VHm+MLqv8fUaZWZaZZWVnZwcXWOLWwk153PBCFp1bNeaFkUNorkNMIrUi0JJw9zJ3Px7oDAwxs36VVqlqQJ3Kexu4+1h3z3T3zLZt2wYRVeLYyu2FXP3cDJo3TmH8DUNpk9Yo7EgidUatHNB191zgc+DMSk9tBLpUeNwZ2FwbmSQxrMou5PKnp1HPjPE3DKVjC13mKlKbgry6qa2ZtYzebwycBiyttNp7wNXRq5yGAXnuviWoTJJYVmUXctnYaZS788qNQ+me3jTsSCJ1TrWubrLIOMtXAD3c/UEz6wp0cPcZB3hZR+AFM6tPpIxed/eJZnYTgLuPAd4HRgArgT3AyMP/T5Fksiq7kEvHTsPdeeXGYfRu3yzsSCJ1UnUvgX0SKAdOAR4ECoC3gMGxXuDu84EBVSwfU+G+A7ccQl6pA1ZuL+SypyMF8eqNw+ilghAJTXVLYqi7DzSzOQDuvsvMGgaYS+ooFYRIfKnuOYmS6GEjh8j5BiJ7FiI1ZkPOHhWESJypbkk8BrwDtDOzh4Avgf8JLJXUOQVFJVw3bibFJWUqCJE4Uq3DTe7+spnNAk4l8tmG8919SaDJpM4oK3duf3UOq3fs5oWRQ1QQInGkWnsSZnYksMbdnwAWAqfvv7xV5Jt6+IMlTFqWzf3n9uXEXulhxxGRCqp7uOktoMzMegLPAN2BVwJLJXXG61kbeHrKGq4ensFVwzLCjiMilVS3JMrdvRS4EHjU3X9M5HMQIodtxpoc7nlnASf2TOe+c/qEHUdEqnAoVzddBlwNTIwu0whrctg25OzhpvGz6NKqCU9cPpAG9TXkt0g8qu5P5khgOPCQu68xs+7A+OBiSTLbWVjMtc/PoLSsnGeuyaRFE/29IRKvqnt102Lg9gqP1wAPBxVKkld+UQlXPzeDjbv28uJ1Q+jRNi3sSCJyANW9uukcM5tjZjlmlm9mBWaWH3Q4SS5795Vx/biZLN9WwJirBjG0R5uwI4nIQVR3WI4/ETlpvSA63pLIISkuLeNH42cxa90u/nzZQL57VLuwI4lINVS3JDYAC1UQcjhKy8q5Y8JcJi/P5ncXHcvZ/XVhnEiiqG5J/Ax438y+AIr3L3T3PwSSSpJGebnzi7cX8MHCrdx79jH8cHDXsCOJyCGobkk8BBQCqYBGf5Vqe2LSSt6YtZHRp/bihpN6hB1HRA5RdUuitbufEWgSSTqfL9vOH/6xnPOPP4I7TusVdhwROQzV/ZzEP8xMJSHVtn7nHkZPmMvRHZrz2wv7E5ncUEQSzUFLIjp16c+AD81sry6BlYPZuy9yJZO7M+bKgTRuWD/sSCJymA56uMnd3czmuvvA2ggkic3dueedBSzdms9z1w4mo03TsCOJyDdQ3cNNU80s5nzWIvu9OHUdb8/ZxI9P663PQogkgeqWxHeBaWa2yszmm9kCM5t/oBeYWRczm2RmS8xskZmNrmKdk80sz8zmRm/3Hc5/hMSHrLU5/HriYk47ph23frdn2HFEpAZU9+qmsw7je5cCP3H32WbWDJhlZp9Ex4GqaIq7n3MY31/iyMrthYx6aRadWzXm9z84nnr1dKJaJBlUd4C/dYf6jd19C7Aler/AzJYAnYDKJSEJbkPOHq58Zjr1zHh+5BBaNNaoriLJolYG8TezbsAAYHoVTw83s3lm9oGZ9Y3x+lFmlmVmWdnZ2QEmlUO1vaCIq56dzp59pbx0/RC6p+tEtUgyCbwkzCyNyPSnd7h75ctmZwMZ7n4c8Gfg3aq+h7uPdfdMd89s27ZtsIGl2vL2lHD1szPYXlDM8yOHcEzH5mFHEpEaFmhJmFkKkYJ42d3frvy8u+e7e2H0/vtAipmlB5lJasbu4lKuHTeD1dm7GXtVJoMyWoUdSUQCEFhJRD+E9yywJNZAgGbWIboeZjYkmmdnUJmkZhSXljHqpSzmb8zjscsGcGIv9bpIsqru1U2H4wTgKmCBmc2NLrsb6Arg7mOAi4GbzawU2AtcquHI49/97y3iq5U7+f0lx3Fmvw5hxxGRAAVWEu7+JXDA6yDd/XHg8aAySM17beZ6Xp2xgVu+eyQXDeocdhwRCVitXN0kyWH+xlx++ddFnNQrnTtPPyrsOCJSC1QSUi05u/dx8/jZtE1rxKOXDqC+PiwnUicEeU5CkkRZuTN6whyyC4p58+bhtG6qeadE6gqVhBzUHz9ZzpQVO3j4wmPp37ll2HFEpBbpcJMc0CeLt/H4pJX8MLMLlw7R/NQidY1KQmKas34Xd0yYQ79OzXngvCpHTBGRJKeSkCot2ZLPtc/PJL1ZI567ZjCpKZpdTqQuUknI16zOLuSqZ2fQOKU+468fSrvmqWFHEpGQqCTkP2zK3cuVz0zH3Rl/w1C6tG4SdiQRCZGubpJ/yS4o5spnplNQXMqrNw6jZ7u0sCOJSMi0JyFAZNjvq56dzta8IsaNHEy/Ti3CjiQicUAlIZSVO7dPmMOq7ELGXj2IQRmtw44kInFCJSE89ukKvlieza++35eTemlSJxH5N5VEHTdp6XYe/XQFFw3szBVD9WE5EflPKok6bP3OPYyeMIdjOjbnN+f3Izr/k4jIv6gk6qiikjJuGj8LgDFXDqRxQ31YTkS+TpfA1kHuzr3vLmTxlnyevSaTjDZNw44kInFKexJ10KszNvDmrI3cfkpPTj2mfdhxRCSOqSTqmA8WbOG+vy7kpF7pjD6td9hxRCTOqSTqkA8WbOHWV+fQv3MLnrxioGaXE5GDCqwkzKyLmU0ysyVmtsjMRlexjpnZY2a20szmm9nAoPLUdfsL4vguLXnhuiE0S00JO5KIJIAgT1yXAj9x99lm1gyYZWafuPviCuucBfSK3oYCT0W/Sg16f8EWbqtQEGmNdL2CiFRPYHsS7r7F3WdH7xcAS4BOlVY7D3jRI6YBLc2sY1CZ6iIVhIh8E7VyTsLMugEDgOmVnuoEbKjweCNfLxLMbJSZZZlZVnZ2dlAxk87Hi7Zy26tzGKCCEJHDFHhJmFka8BZwh7vnV366ipf41xa4j3X3THfPbNtWYwtVx/yNudw+YQ79OrVgnApCRA5ToCVhZilECuJld3+7ilU2Al0qPO4MbA4yU12wKXcv17+QRXpaI565OlMFISKHLcirmwx4Flji7n+Isdp7wNXRq5yGAXnuviWoTHVBQVEJ14+bSdG+Mp67djBtmzUKO5KIJLAg/8Q8AbgKWGBmc6PL7ga6Arj7GOB9YASwEtgDjAwwT9IrLSvn1lfmsGJ7IeNGDqZ3+2ZhRxKRBBdYSbj7l1R9zqHiOg7cElSGusTdeeBvi/lieTb/c8GxmhdCRGqEPnGdJJ77ai0vTVvHqG/34HLNCyEiNURnNBOcu/OXyat5+IOlfK9ve35+5tFhRxKRJKKSSGBl5c6vJy5m3D/Xcnb/jvzhB8dRT+MxiUgNUkkkqKKSMu6YMJcPF23lhhO7c/eIY1QQIlLjVBIJKHfPPm54IYtZ63fxy3P6cP2J3cOOJCJJSiWRYDbl7uXqZ6ezYddeHr9sIGf311BXIhIclUQCyS4o5oqnp5Gzex8vXTeEoT3ahB1JRJKcSiJBFBSVcO3zM9iWX8z4G4YyKKNV2JFEpA7Q5yQSQFFJGTe+mMWyrQU8deVAFYSI1BrtScS50rJyRk+Yw7TVOTx66fGcfFS7sCOJSB2iPYk45u7c++5CPlq0jV99vw/nHf+1qTZERAKlkohT7s4jHy1jwswN3HZKT0aeoMtcRaT26XBTHCouLePedxbyxqyNXD60K3ee3jvsSCJSR6kk4sz2giJuemkWs9fnMvrUXow+tReRqTlERGqfSiKOLNiYx6iXssjdU8KTVwxkxLH6oJyIhEslESfem7eZn74xj/S0Rrx583D6HtEi7EgiIiqJsLk7j3+2kt9/spwh3Vrz5JUDSU/TlKMiEh9UEiFyd37/8XIen7SSCwd24uEL+9OwgS44E5H4oZIIibvz8AdL+cvk1Vw2pCsPnd9PQ32LSNwJ7M9WM3vOzLab2cIYz59sZnlmNjd6uy+oLPHG3Xlw4mL+Mnk1Vw/PUEGISNwKck9iHPA48OIB1pni7ucEmCHulJc79723kPHT1nPdCd355TnH6BJXEYlbge1JuPtkICeo75+I9pWWc/c7Cxg/bT0/+k4PFYSIxL2wz0kMN7N5wGbgLndfVNVKZjYKGAXQtWvXWoxXcxZuyuOuN+axdGsBt53SkztP762CEJG4F2ZJzAYy3L3QzEYA7wK9qlrR3ccCYwEyMzO99iJ+c8WlZTz26QrGfLGaNk0b8vTVmZzep33YsUREqiW0knD3/Ar33zezJ80s3d13hJWpps1Zv4ufvTmfFdsLuXhQZ355dh9aNEkJO5aISLWFVhJm1gHY5u5uZkOInB/ZGVaemuTuPPrpCh77dAXtm6cybuRgzQMhIgkpsJIws1eBk4F0M9sI/ApIAXD3McDFwM1mVgrsBS5195N2kVUAAAldSURBVIQ6lFSVkrJyfv7WAt6avZELB3TigfP60ixVew8ikpgCKwl3v+wgzz9O5BLZpFFYXMrN42cxZcUOfnxab24/tadOTotIQgv76qaksT2/iGufn8mybQU8cnF/fpDZJexIIiLfmEqiBqzcXsA1z81k1559PHtNps4/iEjSUEl8A+7OO3M28cDfFpNSvx6vjRrOsZ01xLeIJA+VxGFasa2Ae99dyPQ1OQzo2pLHLh1Al9ZNwo4lIlKjVBKHaM++Uh77dCXPTFlN00YN+O2Fx/LDzC4aoE9EkpJK4hBMWrade99ZyKbcvVwyqDM/P+to2miCIBFJYiqJaigtK+d/P17GX75YTe/2abxx03AGd2sddiwRkcCpJA5iW34Rt70yhxlrc7h8aFfuO6cPqSn1w44lIlIrVBIH8OWKHYyeMIe9JWX86YfHc/6ATmFHEhGpVSqJKpSVO49/tpI/fbqcnm3TeOrKgfRs1yzsWCIitU4lUcnybQX87M35zN2Qy4UDOvGbC/rRpKE2k4jUTfrtF1VSVs5Tn6/i8c9WkpbagEcvPZ5zjztCYy+JSJ2mkgAWbMzjp29GZo37/nFHcP/3++jSVhERVBI8+flKfv/xcs0aJyJShTpdEn+du4lHPlzGOf078tAFx9KiseZ9EBGpqM6WxKLNefz3W/MZ0r01f/zh8aTUrxd2JBGRuFMnfzPm7N7HqBdn0apJQ564fKAKQkQkhjq3J1FaVs5tr84mu7CYN340nLbNdIJaRCSWOvcn9CMfLeOrlTv5zfn9OK5Ly7DjiIjEtTpVEu/N28zYyau5eniGphcVEamGwErCzJ4zs+1mtjDG82Zmj5nZSjObb2YDg8oCsHhzPj97cx6Du7Xi3rP7BPlWIiJJI8g9iXHAmQd4/iygV/Q2CngqwCwUFpfSIz2NJ64YSMMGdWoHSkTksAX229LdJwM5B1jlPOBFj5gGtDSzjkHlGdK9NRNvO5F2zVKDegsRkaQT5p/UnYANFR5vjC77GjMbZWZZZpaVnZ192G+oKUZFRA5NmCVR1W9sr2pFdx/r7pnuntm2bduAY4mIyH5hlsRGoOIlRp2BzSFlERGRKoRZEu8BV0evchoG5Ln7lhDziIhIJYF94trMXgVOBtLNbCPwKyAFwN3HAO8DI4CVwB5gZFBZRETk8ARWEu5+2UGed+CWoN5fRES+OX1gQEREYlJJiIhITBY56pM4zCwbWFeNVdOBHQHHCYJy1y7lrl2JmhsSN/v+3BnufsifIUi4kqguM8ty98ywcxwq5a5dyl27EjU3JG72b5pbh5tERCQmlYSIiMSUzCUxNuwAh0m5a5dy165EzQ2Jm/0b5U7acxIiIvLNJfOehIiIfEMqCRERiSnpSsLMzjSzZdFpUX8edp4DMbO1ZrbAzOaaWVZ0WWsz+8TMVkS/tgo7J1Q9He2BsprZL6L/BsvM7HvhpI6Z+34z2xTd7nPNbESF5+Ildxczm2RmS8xskZmNji6P621+gNxxvc3NLNXMZpjZvGjuB6LL4317x8pdc9vb3ZPmBtQHVgE9gIbAPKBP2LkOkHctkF5p2SPAz6P3fw78Luyc0SzfBgYCCw+WFegT3faNgO7Rf5P6cZT7fuCuKtaNp9wdgYHR+82A5dF8cb3ND5A7rrc5kflt0qL3U4DpwLAE2N6xctfY9k62PYkhwEp3X+3u+4AJRKZJTSTnAS9E778AnB9iln/xqqejjZX1PGCCuxe7+xoiI/0OqZWglcTIHUs85d7i7rOj9wuAJURmbozrbX6A3LHES25398Low5TozYn/7R0rdyyHnDvZSqLaU6LGCQc+NrNZZjYquqy9R+fViH5tF1q6g4uVNRH+HW41s/nRw1H7DyHEZW4z6wYMIPJXYsJs80q5Ic63uZnVN7O5wHbgE3dPiO0dIzfU0PZOtpKo9pSoceIEdx8InAXcYmbfDjtQDYn3f4engCOB44EtwO+jy+Mut5mlAW8Bd7h7/oFWrWJZaNmryB3329zdy9z9eCKzZA4xs34HWD3ec9fY9k62kkioKVHdfXP063bgHSK7fdvMrCNA9Ov28BIeVKyscf3v4O7boj9Y5cDT/Ht3O65ym1kKkV+0L7v729HFcb/Nq8qdKNscwN1zgc+BM0mA7b1fxdw1ub2TrSRmAr3MrLuZNQQuJTJNatwxs6Zm1mz/feAMYCGRvNdEV7sG+Gs4CaslVtb3gEvNrJGZdQd6ATNCyFel/T/0URcQ2e4QR7nNzIBngSXu/ocKT8X1No+VO963uZm1NbOW0fuNgdOApcT/9q4yd41u79o+Gx/0jciUqMuJnLW/J+w8B8jZg8hVBvOARfuzAm2AT4EV0a+tw84azfUqkd3WEiJ/jVx/oKzAPdF/g2XAWXGW+yVgATA/+kPTMQ5zn0jkMMB8YG70NiLet/kBcsf1Ngf6A3Oi+RYC90WXx/v2jpW7xra3huUQEZGYku1wk4iI1CCVhIiIxKSSEBGRmFQSIiISk0pCRERiUkmIiEhMKgmpU8ys8OBrVev7XGtmjx/g+fPNrE+Fxw+a2Wk18d4itUklIRKM84kMywyAu9/n7v8IMY/IYVFJSJ1lZj81s5nRkTIfqLD83ejIvIsqjM6LmY00s+Vm9gVwwgG+77eAc4H/jU74cqSZjTOzi6PPrzWz/zGzqWaWZWYDzewjM1tlZjcdLJ9IbWoQdgCRMJjZGUTGrRlCZGTM98zs2x6Zf+I6d8+JjoUz08zeIjKJ1QPAICAPmERkOISvcfd/mtl7wER3fzP6fpVX2+Duw83sj8A4IqWTSmSIljEHySdSa1QSUledEb3t/0WfRuSX8mTgdjO7ILq8S3R5B+Bzd88GMLPXgN7f4P33Dzy5gMjMYgVAgZkVRQdsO1A+kVqjkpC6yoDfuvtf/mOh2clERtIc7u57zOxzIn/hQ83OF1Ac/Vpe4f7+xw1i5ROpbTonIXXVR8B10clxMLNOZtYOaAHsihbE0UTmC4bI7Gonm1mb6HwJlxzk+xcQmeO5pvOJ1CrtSUid5O4fm9kxwNTo+YJC4ErgQ+AmM5tPZCjladH1t5jZ/cBUIkOPzwbqH+AtJgBPm9ntwMU1mC+eJ6GSJKShwkVEJCYdbhIRkZh0uEnkGzCze/j6+Yk33P2hMPKI1DQdbhIRkZh0uElERGJSSYiISEwqCRERiUklISIiMf0/Lt3cFTYrdFsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rmses.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
